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GeneViator - Graph VisualizationIt is of big benefit for the common user that the data collectors and source curators at EBI, NCBI and elsewhere diversify their offers. At the first glance, the jungle of data sources wrapped under a convenient user interface is threatening for the average user by its rapid growth. However, thanks to the effort people spend on comfort for users, data source derivatives are being inaugurated that cross-link autonomous data sources for both administrative ease and transparency of content. Not surprising, all these data structures reflect graph types and elements, the beloved progeny of informatics. Once explored, these intrinsic graph structures, especially networks, turn out to be very useful for view creation and many other purposes as well. Data embedded in network nodes and arcs are clearly suited for graphical representation and navigation.
Especially data categories that constitute relationships between two each or more items require potent set-oriented content management, visualization and navigation utilities. Moreover, strategies are needed to discover correlations within and between data sets of independent origin. Whereever data sets possess intrinsic graph structure (e.g. of tree, forest or network type) or can be transposed into such, graphical support is considered indispensable. The Viator tool family depicts large graphs on the whole in a hyperbolic geometry and provides means for set-oriented context mining as well as for correlation discovery across distinct sets at once. Its utility is proven for but not restricted to data from functional genome, transcriptome and proteome research.
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Last update: Tuesday, June 14, 2011
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